JP2014089686A - Vehicle speed estimation apparatus and method - Google Patents

Vehicle speed estimation apparatus and method Download PDF

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JP2014089686A
JP2014089686A JP2012288577A JP2012288577A JP2014089686A JP 2014089686 A JP2014089686 A JP 2014089686A JP 2012288577 A JP2012288577 A JP 2012288577A JP 2012288577 A JP2012288577 A JP 2012288577A JP 2014089686 A JP2014089686 A JP 2014089686A
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vehicle
speed
distance
value
speed estimation
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Hui-Sung Lee
李熙承
Kyung Ho Yoo
劉▲キョン▼虎
Jin Hak Kim
金鎭學
Kyoung Moo Min
閔庚務
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Hyundai Motor Co
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/12—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to parameters of the vehicle itself, e.g. tyre models
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
    • B60W40/105—Speed
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/16—Anti-collision systems
    • G08G1/166—Anti-collision systems for active traffic, e.g. moving vehicles, pedestrians, bikes
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/09—Arrangements for giving variable traffic instructions
    • G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/16—Anti-collision systems
    • G08G1/165—Anti-collision systems for passive traffic, e.g. including static obstacles, trees
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/80—Spatial relation or speed relative to objects
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/80—Spatial relation or speed relative to objects
    • B60W2554/801—Lateral distance
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2555/00—Input parameters relating to exterior conditions, not covered by groups B60W2552/00, B60W2554/00
    • B60W2555/20—Ambient conditions, e.g. wind or rain

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Mathematical Physics (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Traffic Control Systems (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
  • Length Measuring Devices By Optical Means (AREA)

Abstract

PROBLEM TO BE SOLVED: To provide a vehicle speed estimation apparatus and method.SOLUTION: A vehicle speed estimation apparatus and method include: a surrounding environment information acquisition part which acquires vehicle surrounding environment information from at least one sensor arranged in a vehicle; a distance information extraction part which extracts distance information between the vehicle and a vehicle surrounding object from the surrounding environment information acquired via the sensor; a group setting part which classifies the distance information between the vehicle and the vehicle surrounding object on the basis of a preset reference for grouping; a speed calculation part which calculates relative speed between vehicles for each group set in the group setting part; and a speed estimation part which estimates a vehicle speed on the basis of a speed value having the highest occurrence frequency in the relative speeds between vehicles calculated for each group.

Description

本発明は、車速度推定装置及び方法に関し、車と車周辺の固定体間の相対速度に基づき自車の速度を推定する装置及び方法に関する。   The present invention relates to a vehicle speed estimation device and method, and more particularly to a device and method for estimating the speed of a host vehicle based on the relative speed between a vehicle and a stationary body around the vehicle.

一般に、車の速度を推定するにはステアリングホイールに装着された速度センサー又は車の加速度センサーを利用するか、GPSを介して獲得した車の過去及び現在位置の差を利用して推定する。最近は、車底の映像を分析して車の速度を測定するか、車輪にエンコーダを取り付けて車速度を推定することもある。   In general, the speed of a vehicle is estimated using a speed sensor mounted on a steering wheel or an acceleration sensor of the car, or using a difference between the past and current positions of the car acquired via GPS. Recently, an image of the bottom of the vehicle is analyzed to measure the vehicle speed, or an encoder is attached to the wheel to estimate the vehicle speed.

一例として、車の基準速度を推定する技術は、車の走行状況及び制御状況に従い車のエンジントルク情報とブレーキ圧力などのセンサー情報を利用して車の減加速度を推定した後、これを基づき車の基準速度を推定する。   As an example, the technology for estimating the reference speed of a vehicle is based on the estimation of the deceleration of the vehicle using sensor information such as the engine torque information and brake pressure of the vehicle according to the driving state and the control state of the vehicle. Estimate the reference speed.

しかし、車に備えられたセンサーを介して速度を測定する場合、車輪の滑りなどによる誤差が発生することがあり、GPSの場合、陰影地域では速度推定が難しい問題がある。もちろん、車底の映像分析を介して車の速度を測定する方式は映像処理のために高価の装備を備えなければならない。   However, when the speed is measured via a sensor provided in the car, errors due to wheel slipping may occur, and in the case of GPS, there is a problem that speed estimation is difficult in a shaded area. Of course, the method of measuring the speed of the vehicle through image analysis of the bottom of the vehicle must be equipped with expensive equipment for image processing.

韓国公開特許第１０−２０１１−０１１４１２０号公報Korean Published Patent No. 10-2011-0114120

本発明の目的は、車の周辺物体などから取得された距離情報を特定基準に従い同一物体、又は隣接した物体などの距離情報別に分類してグループ化するため、グループ別相対速度の予測が容易になるようにした車速度推定装置及び方法を提供することにある。   The object of the present invention is to classify and group distance information acquired from objects around the vehicle according to a specific standard according to distance information such as the same object or adjacent objects, so that it is easy to predict the relative speed by group. An object of the present invention is to provide a vehicle speed estimation apparatus and method.

さらに、本発明の他の目的は、グループ別に算出された速度値を比べて固定体の速度値を自車の速度で推定するため、速度推定のための別途の装置及びシステムを備えなくとも良く、速度推定演算が簡単な車速度推定装置及び方法を提供することにある。   Furthermore, another object of the present invention is to compare the speed values calculated for each group and to estimate the speed value of the fixed body by the speed of the own vehicle, so that it is not necessary to have a separate device and system for speed estimation. Another object of the present invention is to provide a vehicle speed estimation device and method that can easily calculate a speed.

上記の目的を果たすための本発明に係わる車速度推定装置は、車に備えられた少なくとも一つのセンサーから車の周辺環境情報を取得する周辺環境情報取得部、上記センサーを介して取得された上記周辺環境情報のうち当該車と上記車の周辺物体間の距離情報を抽出する距離情報抽出部、上記車と上記車の周辺物体間の距離情報を既設定された基準に従い分類してグループ化するグループ設定部、上記グループ設定部で設定された各グループ別に上記車の間の相対速度を算出する速度算出部、及び上記グループ別に算出された上記車の間の相対速度のうち発生頻度が最も高い速度値に基づき、上記車の速度を推定する速度推定部を含むことを特徴とする。   In order to achieve the above object, a vehicle speed estimation device according to the present invention includes a surrounding environment information acquisition unit that acquires surrounding environment information of a vehicle from at least one sensor provided in the vehicle, and the above-described sensor acquired via the sensor. A distance information extraction unit that extracts distance information between the vehicle and the surrounding objects of the vehicle from the surrounding environment information, and classifies and groups the distance information between the vehicle and the surrounding objects of the vehicle according to preset criteria. A group setting unit, a speed calculating unit that calculates a relative speed between the vehicles for each group set by the group setting unit, and a highest occurrence frequency among the relative speeds between the vehicles calculated for each group A speed estimation unit for estimating the speed of the vehicle based on a speed value is included.

上記周辺物体は固定体を含み、上記発生頻度が最も高い速度値は、上記車周辺に位置した固定体と上記車の間の相対速度値であることを特徴とする。   The peripheral object includes a fixed body, and the speed value having the highest occurrence frequency is a relative speed value between the fixed body located around the vehicle and the vehicle.

上記グループ設定部は、上記周辺物体の相対位置及び連続する距離値の変化を基準に上記距離情報を分類することを特徴とする。   The group setting unit classifies the distance information based on a relative position of the peripheral object and a continuous change in distance value.

このとき、上記グループ設定部は、上記距離情報を取得した位置及び距離値に基づき、 互いに近接して隣合う位置の距離値の差が基準値以内であれば同一グループに分類し、 互いに近接して隣合う位置の距離値の差が基準値を超過すれば互いに異なるグループに分類することを特徴とする。   At this time, based on the position and distance value from which the distance information is acquired, the group setting unit classifies the same group if the difference between the distance values of adjacent positions that are close to each other is within a reference value and closes to each other. If the difference between the distance values of adjacent positions exceeds a reference value, they are classified into different groups.

上記センサーは、LIDAR、ToF カメラなど物体の距離値を多数のデータで伝送するセンサーのうち少なくとも一つを含むことを特徴とする。   The sensor includes at least one of sensors that transmit a distance value of an object as a large number of data, such as a LIDAR or a ToF camera.

一方、 上記の目的を果たすための本発明に係わる車速度推定方法は、車に備えられた少なくとも一つのセンサーから車の周辺環境情報を取得する段階、上記センサーを介して取得された上記周辺環境情報のうち当該車と上記車の周辺物体間の距離情報を抽出する段階、上記車と上記車の周辺物体間の距離情報を既設定された基準に従い分類してグループ化する段階、上記グループ化された各グループ別に上記車の間の相対速度を算出する段階、及び上記グループ別に算出された上記車の間の相対速度のうち発生頻度が最も高い速度値に基づき、上記車の速度を推定する段階を含むことを特徴とする。   On the other hand, the vehicle speed estimation method according to the present invention for achieving the above object includes a step of acquiring vehicle surrounding environment information from at least one sensor provided in the vehicle, and the surrounding environment acquired through the sensor. Extracting the distance information between the vehicle and the surrounding object of the vehicle from the information, classifying the distance information between the vehicle and the surrounding object of the vehicle according to a preset criterion, and grouping the information, the grouping Calculating the relative speed between the vehicles for each group, and estimating the speed of the vehicle based on the speed value with the highest occurrence frequency among the relative speeds calculated between the groups. Characterized in that it includes stages.

本発明に従えば、車の周辺物体などから取得された距離情報を特定基準に従い同一物体又は隣接した物体などの距離情報別に分類してグループ化するため、グループ別相対速度の予測が容易であり、グループ別に算出された速度値を比べて固定体の速度値を自車の速度で推定するためより正確な速度を推定することができ、 速度推定のための別途の装置及びシステムを備えなくとも良いので費用節減の効果があり、速度推定演算が簡単な長所がある。   According to the present invention, distance information acquired from surrounding objects of a car is classified and grouped according to distance information such as the same object or an adjacent object according to a specific standard, so that it is easy to predict the relative speed by group. Compared with the speed values calculated for each group, the speed value of the fixed body is estimated by the speed of the own vehicle, so that a more accurate speed can be estimated, and there is no need for a separate device and system for speed estimation. Since it is good, it has the effect of reducing costs and has the advantage that the speed estimation calculation is simple.

本発明に係わる車速度推定装置の構成を説明するのに参照される図である。It is a figure referred in order to demonstrate the structure of the vehicle speed estimation apparatus concerning this invention. 本発明に係わる車速度推定装置の構成を示したブロック図である。It is the block diagram which showed the structure of the vehicle speed estimation apparatus concerning this invention. 本発明に係わる車速度推定装置の周辺物体間の相対速度算出動作を説明するのに参照される例示図である。It is an illustration figure referred in order to explain the relative speed calculation operation between the peripheral objects of the vehicle speed estimation apparatus according to the present invention. 本発明に係わる車速度推定装置の周辺物体間の相対速度算出動作を説明するのに参照される例示図である。It is an illustration figure referred in order to explain the relative speed calculation operation between the peripheral objects of the vehicle speed estimation apparatus according to the present invention. 本発明に係わる車速度推定装置の周辺物体間の相対速度算出動作を説明するのに参照される例示図である。It is an illustration figure referred in order to explain the relative speed calculation operation between the peripheral objects of the vehicle speed estimation apparatus according to the present invention. 本発明に係わる車速度推定装置の周辺物体間の相対速度算出動作を説明するのに参照される例示図である。It is an illustration figure referred in order to explain the relative speed calculation operation between the peripheral objects of the vehicle speed estimation apparatus according to the present invention. 本発明に係わる車速度推定方法に対する動作流れを示したフローチャートである。3 is a flowchart showing an operation flow for a vehicle speed estimation method according to the present invention.

以下、図を参照して本発明の実施例を説明する。   Embodiments of the present invention will be described below with reference to the drawings.

図1は、本発明に係わる車速度推定装置の構成を説明するのに参照される図である。図1を参照すれば、車10には、車10の周辺環境を感知する少なくとも一つの周辺環境感知センサー15が備えられ、車10の停車時、又は、車10の走行中に周辺環境感知センサー15を介して車10の周辺環境情報を感知する。このとき、 周辺環境感知センサー15は LIDAR、ToF カメラなど物体の距離値を多数のデータで伝送するセンサーのうち少なくとも一つを含み、 周辺環境感知センサー15を介して感知された周辺環境情報は周辺物体などに対する距離情報を含む。   FIG. 1 is a diagram which is referred to for explaining the configuration of a vehicle speed estimation apparatus according to the present invention. Referring to FIG. 1, the vehicle 10 includes at least one surrounding environment detection sensor 15 that detects the surrounding environment of the vehicle 10, and the surrounding environment detection sensor when the vehicle 10 is stopped or during the traveling of the vehicle 10. The surrounding environment information of the car 10 is sensed through 15. At this time, the surrounding environment detection sensor 15 includes at least one of sensors that transmit the distance value of an object such as a LIDAR or a ToF camera as a lot of data, and the surrounding environment information detected through the surrounding environment detection sensor 15 is Contains distance information for objects.

ここで、周辺物体は移動体(M) 及び固定体(F)が該当され得、周辺に移動体(M)のない場合は固定体(F)のみ該当され得ることもある。言い換えれば、本発明は自車の正確な速度推定のために必ず車10 周辺に固定体(F)が位置したものと仮定し、好ましくは、車10周辺に多数の固定体(F)が位置したものとする。   Here, the peripheral object may correspond to the moving body (M) and the fixed body (F), and if there is no moving body (M) in the periphery, only the fixed body (F) may correspond. In other words, the present invention assumes that a fixed body (F) is always positioned around the vehicle 10 for accurate speed estimation of the host vehicle, and preferably a large number of fixed bodies (F) are positioned around the vehicle 10. Shall be.

一例として、車10の周辺環境感知センサー15は図1に示されたところのように、 車10の側面又は対角線側面に位置した固定体などからの距離情報及び車10 前方の移動体などからの距離情報を感知することになる。   As an example, as shown in FIG. 1, the ambient environment sensor 15 of the car 10 includes distance information from a fixed body or the like located on the side surface or diagonal side surface of the car 10 and from a moving body in front of the car 10. It will sense distance information.

このとき、車速度推定装置は、車10に備えられた少なくとも一つの周辺環境感知センサー15を介して感知される周辺環境情報を取得し、周辺環境情報のうち距離情報を抽出して既設定された条件に従いグループ化した後に、各グループ別相対速度値を比べて頻度数の高い速度値を自車の速度で推定する。   At this time, the vehicle speed estimation device acquires the surrounding environment information sensed through at least one surrounding environment detection sensor 15 provided in the vehicle 10, and extracts the distance information from the surrounding environment information and is already set. After grouping according to the above-mentioned conditions, the relative speed value for each group is compared, and a speed value with a high frequency is estimated based on the speed of the vehicle.

ここに、本発明に係わる車速度推定装置に対する具体的な構成説明は図2を参照することにする。   Here, FIG. 2 will be referred to for a specific description of the vehicle speed estimation apparatus according to the present invention.

図2は、本発明に係わる車速度推定装置の構成を示したブロック図である。   FIG. 2 is a block diagram showing the configuration of the vehicle speed estimation apparatus according to the present invention.

図2を参照すれば、本発明に係わる車速度推定装置100は制御部110、周辺環境情報取得部120、出力部130、貯蔵部140、距離情報抽出部150、グループ設定部160、 速度算出部170 及び速度推定部180を含む。ここで、制御部110は、車速度推定装置100の各部の動作を制御する。   Referring to FIG. 2, the vehicle speed estimation apparatus 100 according to the present invention includes a control unit 110, a surrounding environment information acquisition unit 120, an output unit 130, a storage unit 140, a distance information extraction unit 150, a group setting unit 160, a speed calculation unit. 170 and a speed estimation unit 180 are included. Here, the control unit 110 controls the operation of each unit of the vehicle speed estimation device 100.

周辺環境情報取得部120は、車に備えられた少なくとも一つの周辺環境感知センサー15と連結され、 周辺環境感知センサー15から車の周辺環境情報を取得する。前述したように、 周辺環境感知センサー15は LIDAR 及び ToF などのように距離測定のためのセンサーを少なくとも一つ含み、周辺環境感知センサー15を介して感知された周辺環境情報は周辺物体などに対する距離情報を含む。好ましくは、周辺環境情報は、車周辺の固定体に対する距離情報を含む。   The surrounding environment information acquisition unit 120 is connected to at least one surrounding environment detection sensor 15 provided in the vehicle, and acquires the surrounding environment information of the vehicle from the surrounding environment detection sensor 15. As described above, the surrounding environment detection sensor 15 includes at least one sensor for distance measurement such as LIDAR and ToF, and the surrounding environment information detected through the surrounding environment detection sensor 15 is the distance to the surrounding object. Contains information. Preferably, the surrounding environment information includes distance information for a fixed body around the vehicle.

出力部130は、車速度推定装置100の動作状態データ及び車速度推定結果を出力する。 ここで、出力部130はディスプレイ、スピーカーなどが該等され得、 車速度推定結果をディスプレイ上に表示するか、スピーカーを介して音声信号で出力することができる。   The output unit 130 outputs the operation state data of the vehicle speed estimation device 100 and the vehicle speed estimation result. Here, the output unit 130 may be a display, a speaker, or the like, and the vehicle speed estimation result may be displayed on the display or output as an audio signal through the speaker.

貯蔵部140は、車速度推定装置100の動作のための設定値などが貯蔵され、 動作結果値、例えば、周辺環境情報、グループ情報及び速度情報などが貯蔵され得る。   The storage unit 140 stores setting values for the operation of the vehicle speed estimation apparatus 100, and may store operation result values such as surrounding environment information, group information, and speed information.

距離情報抽出部150は、周辺環境感知センサー15を介して取得された周辺環境情報のうち距離情報を抽出する。さらに詳しくは、車の周辺に位置した周辺物体など、例えば、 移動体及び固定体に対する距離情報を抽出する。   The distance information extraction unit 150 extracts distance information from the surrounding environment information acquired through the surrounding environment detection sensor 15. More specifically, distance information for a moving object and a fixed object such as a peripheral object located around the vehicle is extracted.

グループ設定部160は、周辺物体などに対する距離情報を既設定された基準に従い分類してグループ化する。このとき、グループ設定部160は周辺物体の相対位置及び連続する位置の距離値の変化を基準に距離情報を分類する。さらに詳しくは、グループ設定部160は距離情報を取得した位置及び距離値に基づき、互いに近接に隣合う位置の距離値の差が基準値以内であれば同一グループに分類し、互いに近接して隣合う位置の距離値の差が基準値を超過すれば互いに異なるグループに分類する。   The group setting unit 160 classifies distance information with respect to surrounding objects and the like according to a preset criterion. At this time, the group setting unit 160 classifies the distance information based on the relative position of the surrounding objects and the change in the distance value between successive positions. More specifically, based on the position and distance value from which the distance information is acquired, the group setting unit 160 classifies the same group if the difference in the distance value between adjacent positions is within a reference value, and adjacent to each other. If the difference in the distance value of the matching position exceeds the reference value, it is classified into different groups.

速度算出部170は、グループ設定部160で設定された各グループ別に車と周辺物体の間の相対速度を算出する。 一例として、速度算出部170は各グループの距離変化ベクトルを時間で分けて車と各グループ内の周辺物体間の相対速度を算出する。   The speed calculation unit 170 calculates the relative speed between the vehicle and the surrounding object for each group set by the group setting unit 160. As an example, the speed calculating unit 170 calculates the relative speed between the vehicle and the surrounding objects in each group by dividing the distance change vector of each group by time.

速度推定部180は、速度算出部170により算出された各グループの相対速度値のうち発生頻度が最も高い速度値に基づき自車の速度を推定する。ここで、 車周辺には移動体より固定体が多いものに仮定するため、発生頻度が最も高い速度値は、車周辺に位置した固定体と車の間の相対速度値となる。   The speed estimation unit 180 estimates the speed of the host vehicle based on the speed value with the highest occurrence frequency among the relative speed values of each group calculated by the speed calculation unit 170. Here, since it is assumed that there are more stationary bodies than moving bodies around the car, the speed value with the highest occurrence frequency is the relative speed value between the stationary body and the car located around the car.

場合に応じては、速度推定部180は一定時間の間に抽出された速度値、 すなわち、 各グループの相対速度値のうち発生頻度が最も高い速度値などの平均値を自車の速度で推定するか、一時的に平均値で差が多く出る速度値が抽出される場合は誤算出と見做すこともできる。   In some cases, the speed estimation unit 180 estimates the speed value extracted during a certain period of time, that is, the average value such as the speed value with the highest occurrence frequency among the relative speed values of each group based on the speed of the host vehicle. Or, if a speed value that has a large difference in average value is extracted temporarily, it can be regarded as an erroneous calculation.

図3ないし5は、本発明に係わる車速度推定装置の周辺物体間の相対速度算出動作を説明するのに参照される例示図である。   3 to 5 are exemplary diagrams referred to for explaining the relative speed calculation operation between the surrounding objects of the vehicle speed estimation apparatus according to the present invention.

先ず、図3は、車10の移動時、周辺から取得された距離情報をグループ化する実施例を現わしたものである。 図3を参照すれば、 車10は(a)のように現在位置で周辺環境情報を取得し、 車速度推定装置はこのとき取得された周辺環境情報のうち距離情報を抽出してグループ化する。   First, FIG. 3 shows an embodiment in which distance information acquired from the vicinity is grouped when the vehicle 10 moves. Referring to FIG. 3, the car 10 acquires the surrounding environment information at the current position as shown in (a), and the vehicle speed estimation device extracts the distance information from the acquired surrounding environment information and groups it. .

一例として、車速度推定装置は、車10の左側方向に位置した固定体からの距離情報をG1にグループ化し、左側対角線方向に位置した移動体からの距離情報をG2にグループ化する。このとき、固定体からの距離情報と移動体からの距離情報は互いに隣合う位置や距離変化の差が大きいため互いに異なるグループに分類する。   As an example, the vehicle speed estimation device groups distance information from a stationary body located in the left direction of the vehicle 10 into G1, and groups distance information from a moving body located in the left diagonal direction into G2. At this time, the distance information from the fixed body and the distance information from the moving body are classified into groups different from each other because there are large differences in positions adjacent to each other and distance changes.

同様に、車速度推定装置は、車10の右側対角線方向に位置した移動体からの距離情報を G3にグループ化し、右側対角線方向に位置した固定体からの距離情報を G4にグループ化し、右側方向に位置した固定体からの距離情報を G5にグループ化する。   Similarly, the vehicle speed estimation device groups the distance information from the moving body located in the right diagonal direction of the car 10 into G3, and the distance information from the fixed body located in the right diagonal direction into G4, The distance information from the fixed body located at is grouped into G5.

このとき、右側対角線方向に位置した移動体からの距離情報と固定体からの距離情報は互いに隣合う位置や距離変化の差が大きいため互いに異なるグループに分類する。さらに、右側対角線方向に位置した固定体と右側方向に位置した固定体からの距離情報を互いに隣合う位置や距離変化の差が大きいため互いに異なるグループに分類する。若し、 二つの固定体が互いに近接していて距離変化の差が大きくなければ、 二つの固定体からの距離情報を一つのグループにグループ化することもできる。   At this time, the distance information from the moving body located in the right diagonal direction and the distance information from the fixed body are classified into different groups because there is a large difference between the adjacent positions and distance changes. Further, the distance information from the fixed body positioned in the right diagonal direction and the fixed body positioned in the right direction is classified into different groups because of the large difference in the position adjacent to each other and the distance change. If the two fixed bodies are close to each other and the difference in distance is not large, the distance information from the two fixed bodies can be grouped into one group.

図3の(a)のように距離情報をグループ化した状態で車10が走行することになれば、 (b)のように車10と移動体の位置が変化することになり、 固定体の位置はそのまま固定されるようになる。   If the vehicle 10 travels with the distance information grouped as shown in (a) of Fig. 3, the positions of the vehicle 10 and the moving body change as shown in (b). The position is fixed as it is.

図3の(b)で車10は時間当りaほど移動し、 G2の移動体は時間当りbほど移動し、G3の移動体は時間当りcほど移動する。したがって、車10の移動に伴い車10の周辺の移動体及び固定体に対する距離変化ベクトルは互いに異なることになる。この場合、車速度推定装置は各グループ別距離変化ベクトルを利用して速度を算出する。このとき、車速度推定装置により算出された速度情報は図4と同一である。   In FIG. 3 (b), the car 10 moves about a per hour, the G2 moving body moves about b per hour, and the G3 moving body moves about c per hour. Accordingly, as the vehicle 10 moves, the distance change vectors for the moving body and the fixed body around the vehicle 10 are different from each other. In this case, the vehicle speed estimation device calculates the speed using the distance change vector for each group. At this time, the speed information calculated by the vehicle speed estimation device is the same as in FIG.

図4を参照すれば、G1グループの固定体は位置が固定されるため車10の距離変化ベクトルに基づき速度を算出する。このとき、算出された G1 グループの速度は-aとなる。 G4 グループ及び G5グループも同様に固定体の位置が変化しないため車10の距離変化ベクトルに基づき速度を算出し、このとき算出された速度は全て-aとなる。   Referring to FIG. 4, since the position of the fixed body of the G1 group is fixed, the speed is calculated based on the distance change vector of the vehicle 10. At this time, the calculated speed of the G1 group is -a. Similarly, in the G4 group and the G5 group, since the position of the stationary body does not change, the speed is calculated based on the distance change vector of the vehicle 10, and the calculated speeds are all -a.

一方、G2グループの移動体は時間当りbほど移動し、車10は時間当りaほど移動するため、G2グループの移動体と車10の距離変化ベクトルに基づき速度を算出する。このとき、 算出されたG2グループの速度は b-aとなる。   On the other hand, since the mobile body of the G2 group moves about b per hour and the car 10 moves about a per time, the speed is calculated based on the distance change vector between the mobile body of the G2 group and the car 10. At this time, the calculated speed of the G2 group is b-a.

さらに、G3グループの移動体は時間当りcほど移動し、車10の時間当り a ほど移動するため、G3グループの移動体と車10の距離変化ベクトルに基づき速度を算出する。このとき、算出されたG3グループの速度はc-aとなる。   Further, since the G3 group moving body moves about c per hour and the vehicle 10 moves about a per hour, the speed is calculated based on the distance change vector between the G3 group moving body and the car 10. At this time, the calculated speed of the G3 group is c-a.

図4の場合、各グループ別に算出された速度値のうち-aの頻度が最も高いため、 車速度推定装置は-aを当該車の速度で推定することができる。   In the case of FIG. 4, since the frequency of -a is the highest among the speed values calculated for each group, the vehicle speed estimation device can estimate -a with the speed of the vehicle.

図5及び図6は図3及び図4の他の実施例であって、曲線道路で車速度を推定する動作を現わしたものである。 図5を参照すれば、車は、車周辺に位置した四つの固定体と二つの移動体に対する距離情報を取得すれば、車速度推定装置は取得された距離情報をグループ化する。   FIGS. 5 and 6 are other embodiments of FIGS. 3 and 4 and show the operation of estimating the vehicle speed on a curved road. Referring to FIG. 5, if a vehicle acquires distance information for four fixed bodies and two moving bodies located around the vehicle, the vehicle speed estimation device groups the acquired distance information.

一例として、 図5は左側から右側方向に第1固定体、 第2固定体、 第3固定体及び第4固定体、同様に左側から右側方向に第1移動体及び第2移動体と仮定する。   As an example, FIG. 5 assumes a first fixed body, a second fixed body, a third fixed body, and a fourth fixed body from the left side to the right side, and similarly, a first moving body and a second mobile body from the left side to the right side. .

このとき、車速度推定装置は第1固定体に対する距離情報をG1にグループ化し、第1 移動体に対する距離情報をG2にグループ化し、 第2固定体に対する距離情報をG3にグループ化し、 第2移動体に対する距離情報をG4にグループ化し、 第3固定体に当該距離情報をG5にグループ化し、第4固定体に対する距離情報をG6にグループ化する。   At this time, the vehicle speed estimation device groups the distance information for the first fixed body into G1, groups the distance information for the first movable body into G2, groups the distance information about the second fixed body into G3, and moves the second movement. The distance information for the body is grouped into G4, the distance information for the third fixed body is grouped with G5, and the distance information for the fourth fixed body is grouped with G6.

図5の(b)のように、所定時間が経過すれば車10は時間当り a ほど移動し、 G2の第2移動体は時間当りbほど移動し、G3の第3移動体は時間当りcほど移動する。したがって、車10が移動するに伴い車10 周辺の第1移動体、 第2移動体及び固定体などに対する距離変化ベクトルは互いに異なることになる。   As shown in (b) of FIG. 5, when the predetermined time has elapsed, the car 10 moves about a per hour, the second moving body of G2 moves about b per hour, and the third moving body of G3 moves c per hour. Move about. Therefore, as the vehicle 10 moves, the distance change vectors for the first moving body, the second moving body, and the fixed body around the vehicle 10 are different from each other.

この場合、車速度推定装置は各グループ別距離変化ベクトルを利用して速度を算出し、それぞれの距離変化ベクトルに基づき算出されたグループ別速度は図6と同一である。   In this case, the vehicle speed estimation device calculates the speed using the group-specific distance change vectors, and the group-specific speeds calculated based on the distance change vectors are the same as those in FIG.

図6を参照すれば、G1、G3、G5及びG6グループの固定体は位置が固定されるため車の距離変化ベクトルに基づき速度を算出し、このとき算出された G1、 G3、 G5 及び G6 グループの速度は全て-aとなる。   Referring to FIG. 6, the fixed body of the G1, G3, G5 and G6 groups is fixed in position, so the speed is calculated based on the vehicle distance change vector, and the G1, G3, G5 and G6 groups calculated at this time are calculated. All speeds are -a.

一方、第1移動体は時間当りbほど移動し、車は時間当り a ほど移動するため、 第1移動体と車の距離変化ベクトルに基づきG2グループの速度を算出し、このとき算出されたG2グループの速度は b-aとなる。さらに、第2移動体は時間当りcほど移動し、車の時間当りaほど移動するため、第2移動体と車の距離変化ベクトルに基づきG4グループの速度を算出し、このとき算出されたG4グループの速度はc-aとなる。   On the other hand, since the first moving body moves about b per hour and the car moves about a per hour, the speed of the G2 group is calculated based on the distance change vector between the first moving body and the car, and the calculated G2 The group speed is ba. Further, since the second moving body moves about c per hour and moves about a per hour of the car, the speed of the G4 group is calculated based on the distance change vector between the second moving body and the car, and the G4 calculated at this time is calculated. The group speed is ca.

図6の場合にも、各グループ別に算出された速度値のうち-aの頻度が最も高いため、車速度推定装置は-aを当該車の速度で推定することができる。   Also in the case of FIG. 6, since the frequency of -a is the highest among the speed values calculated for each group, the vehicle speed estimation device can estimate -a with the speed of the vehicle.

上記のように構成される本発明に係わる車速度推定装置の動作流れをより詳しく説明すれば次の通りである。   The operation flow of the vehicle speed estimation apparatus according to the present invention configured as described above will be described in more detail as follows.

図7は、本発明に係わる車速度推定方法に対する動作流れを示したフローチャートである。図7を参照すれば、本発明に係わる車速度推定装置は、車に備えられた周辺環境感知センサーを介して周辺環境情報を取得する(S100)。   FIG. 7 is a flowchart showing an operation flow for the vehicle speed estimation method according to the present invention. Referring to FIG. 7, the vehicle speed estimation apparatus according to the present invention acquires the surrounding environment information through the surrounding environment detection sensor provided in the vehicle (S100).

このとき、 車速度推定装置は「S100」過程で取得された周辺環境情報のうち周辺物体間の距離情報を獲得し(S110)、 既設定された基準、 例えば、 周辺物体の相対位置及び連続する距離値の変化程度などに従い「S110」過程で獲得した距離情報をグループ化する(S120)。   At this time, the vehicle speed estimation device acquires the distance information between the surrounding objects from the surrounding environment information acquired in the process of “S100” (S110), and sets the reference, for example, the relative position of the surrounding objects and the continuous information. The distance information acquired in the “S110” process is grouped according to the degree of change of the distance value (S120).

以後、 車速度推定装置は周辺物体及び車の距離変化ベクトルを利用して「S120」過程での各グループ別に速度を算出し(S130)、「S130」過程で算出された値のうち発生頻度が最も高い速度値を抽出して(S140)、自車の速度で推定する(S150)。   Thereafter, the vehicle speed estimation device calculates the speed for each group in the “S120” process using the distance change vector of the surrounding object and the car (S130), and the occurrence frequency of the values calculated in the “S130” process is The highest speed value is extracted (S140) and estimated by the speed of the host vehicle (S150).

「S100」ないし「S150」過程は、車走行時、別途の終了命令が入力される前まで繰り返して行われ、 終了命令が入力されると(S160) 関連動作を全て終了する。   The “S100” to “S150” processes are repeated until a separate end command is input when the vehicle is traveling. When the end command is input (S160), all related operations are ended.

以上のように、本発明に係わる車速度推定装置及び方法は例示された図を参照して説明したが、 本明細書に開示された実施例と図により本発明は限定されず、 技術思想が保護される範囲内で応用され得る。   As described above, the vehicle speed estimation apparatus and method according to the present invention have been described with reference to the drawings. However, the present invention is not limited to the embodiments and the figures disclosed in the present specification, and the technical idea is not limited. It can be applied within the scope to be protected.

10: 車
15: 周辺環境感知センサー
100: 車速度推定装置
110: 制御部
120: 周辺環境情報取得部
130: 出力部
140: 貯蔵部
150: 距離情報抽出部
160: グループ設定部
170: 速度算出部
180: 速度推定部
F: 固定体
M:移動体 10: Car
15: Ambient environment sensor
100: Vehicle speed estimation device
110: Control unit
120: Ambient environment information acquisition department
130: Output section
140: Storage
150: Distance information extraction unit
160: Group setting section
170: Speed calculator
180: Speed estimation part
F: Fixed body
M: Mobile object

Claims (9)

車に備えられた少なくとも一つのセンサーから車の周辺環境情報を取得する周辺環境情報取得部;
上記センサーを介して取得された上記周辺環境情報のうち当該車と上記車の周辺物体間の距離情報を抽出する距離情報抽出部;
上記車と上記車の周辺物体間の距離情報を既設定された基準に従い分類してグループ化するグループ設定部;
上記グループ設定部で設定された各グループ別に上記車の間の相対速度を算出する速度算出部; 及び
上記グループ別に算出された上記車の間の相対速度のうち発生頻度が最も高い速度値に基づき、上記車の速度を推定する速度推定部を含むことを特徴とする車速度推定装置。 A surrounding environment information acquisition unit that acquires surrounding environment information of the vehicle from at least one sensor provided in the vehicle;
A distance information extraction unit for extracting distance information between the vehicle and the surrounding objects of the vehicle from the surrounding environment information acquired through the sensor;
A group setting unit for classifying and grouping distance information between the vehicle and objects around the vehicle according to a predetermined standard;
A speed calculating unit for calculating a relative speed between the vehicles for each group set by the group setting unit; and a speed value having the highest occurrence frequency among the relative speeds calculated for each group. A vehicle speed estimation device including a speed estimation unit for estimating the speed of the vehicle. 上記周辺物体は固定体を含み、
上記発生頻度が最も高い速度値は、上記車周辺に位置した固定体と上記車の間の相対速度値であることを特徴とする請求項１記載の車速度推定装置。 The surrounding objects include a fixed body,
2. The vehicle speed estimation apparatus according to claim 1, wherein the speed value having the highest occurrence frequency is a relative speed value between a stationary body located around the vehicle and the vehicle. 上記グループ設定部は、
上記周辺物体の相対位置及び連続する距離値の変化を基準に上記距離情報を分類することを特徴とする請求項１記載の車速度推定装置。 The group setting section
2. The vehicle speed estimation apparatus according to claim 1, wherein the distance information is classified based on a relative position of the peripheral object and a continuous change in distance value. 上記グループ設定部は、
上記距離情報を取得した位置及び距離値に基づき、互いに近接して隣合う位置の距離値の差が基準値以内であれば同一グループに分類し、互いに近接して隣合う位置の距離値の差が基準値を超過すれば互いに異なるグループに分類することを特徴とする請求項３記載の車速度推定装置。 The group setting section
Based on the position and distance value from which the distance information was acquired, if the difference in distance value between adjacent positions is within the reference value, classify them into the same group and the difference in distance value between adjacent positions The vehicle speed estimation device according to claim 3, wherein if the vehicle exceeds a reference value, the vehicle is classified into different groups. 上記センサーは、
上記周辺物体の距離値を感知するセンサーであることを特徴とする請求項１記載の車速度推定装置。 The sensor
2. The vehicle speed estimation device according to claim 1, wherein the vehicle speed estimation device is a sensor that senses a distance value of the peripheral object. 車に備えられた少なくとも一つのセンサーから車の周辺環境情報を取得する段階;
上記センサーを介して取得された上記周辺環境情報のうち当該車と上記車の周辺物体間の距離情報を抽出する段階;
上記車と上記車の周辺物体間の距離情報を既設定された基準に従い分類してグループ化する段階;
上記グループ化された各グループ別に上記車の間の相対速度を算出する段階; 及び
上記グループ別に算出された上記車の間の相対速度のうち発生頻度が最も高い速度値に基づき、上記車の速度を推定する段階を含むことを特徴とする車速度推定方法。 Obtaining information on the surrounding environment of the vehicle from at least one sensor provided on the vehicle;
Extracting distance information between the vehicle and the surrounding objects of the vehicle from the surrounding environment information acquired through the sensor;
Categorizing and grouping distance information between the vehicle and surrounding objects of the vehicle according to preset criteria;
Calculating a relative speed between the vehicles for each of the grouped groups; and a speed of the vehicle based on a speed value having the highest occurrence frequency among the relative speeds calculated for the groups. A vehicle speed estimation method comprising the step of estimating the vehicle speed. 上記周辺物体は固定体を含み、
上記発生頻度が最も高い速度値は、上記車周辺に位置した固定体と上記車の間の相対速度値であることを特徴とする請求項６記載の車速度推定方法。 The surrounding objects include a fixed body,
The vehicle speed estimation method according to claim 6, wherein the speed value having the highest occurrence frequency is a relative speed value between a stationary body located around the vehicle and the vehicle. 上記グループ化する段階は、
上記周辺物体の相対位置及び連続する距離値の変化を基準に上記距離情報を分類することを特徴とする請求項６記載の車速度推定方法。 The grouping stage is
7. The vehicle speed estimation method according to claim 6, wherein the distance information is classified based on a relative position of the peripheral object and a continuous change in distance value. 上記グループ化する段階は、
上記距離情報を取得した位置及び距離値に基づき、互いに近接して隣合う位置の距離値の差が基準値以内であれば同一グループに分類し、 互いに近接して隣合う位置の距離値の差が基準値を超過すれば互いに異なるグループに分類することを特徴とする請求項８記載の車速度推定方法。 The grouping stage is
Based on the position and distance value obtained from the above distance information, if the difference in the distance value between adjacent positions is within the reference value, classify them into the same group, and the difference between the distance values between adjacent positions 9. The vehicle speed estimation method according to claim 8, wherein if the vehicle exceeds a reference value, the vehicle is classified into different groups.
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